Swift Logic for Big Data and Knowledge Graphs: Overview of Requirements, Language, and System
Many modern companies wish to maintain knowledge in the form of a corporate knowledge
graph and to use and manage this knowledge via a knowledge graph management system …
graph and to use and manage this knowledge via a knowledge graph management system …
{RStream}: Marrying relational algebra with streaming for efficient graph mining on a single machine
Graph mining is an important category of graph algorithms that aim to discover structural
patterns such as cliques and motifs in a graph. While a great deal of work has been done …
patterns such as cliques and motifs in a graph. While a great deal of work has been done …
Handling iterations in distributed dataflow systems
Over the past decade, distributed dataflow systems (DDS) have become a standard
technology. In these systems, users write programs in restricted dataflow programming …
technology. In these systems, users write programs in restricted dataflow programming …
Knowledge graphs and enterprise AI: the promise of an enabling technology
L Bellomarini, D Fakhoury, G Gottlob… - 2019 IEEE 35th …, 2019 - ieeexplore.ieee.org
Adopting a mature AI strategy is fundamental for modern knowledge companies to govern
the proliferation of smart AI-driven applications and to coordinate them within coherent …
the proliferation of smart AI-driven applications and to coordinate them within coherent …
Graspan: A single-machine disk-based graph system for interprocedural static analyses of large-scale systems code
There is more than a decade-long history of using static analysis to find bugs in systems
such as Linux. Most of the existing static analyses developed for these systems are simple …
such as Linux. Most of the existing static analyses developed for these systems are simple …
Synthesizing datalog programs using numerical relaxation
The problem of learning logical rules from examples arises in diverse fields, including
program synthesis, logic programming, and machine learning. Existing approaches either …
program synthesis, logic programming, and machine learning. Existing approaches either …
Syntax-guided synthesis of datalog programs
Datalog has witnessed promising applications in a variety of domains. We propose a
programming-by-example system, ALPS, to synthesize Datalog programs from input-output …
programming-by-example system, ALPS, to synthesize Datalog programs from input-output …
Flan: an expressive and efficient datalog compiler for program analysis
Datalog has gained prominence in program analysis due to its expressiveness and ease of
use. Its generic fixpoint resolution algorithm over relational domains simplifies the …
use. Its generic fixpoint resolution algorithm over relational domains simplifies the …
Bring your own data structures to Datalog
A Sahebolamri, L Barrett, S Moore… - Proceedings of the ACM …, 2023 - dl.acm.org
The restricted logic programming language Datalog has become a popular implementation
target for deductive-analytic workloads including social-media analytics and program …
target for deductive-analytic workloads including social-media analytics and program …
Convergence of datalog over (pre-) semirings
Recursive queries have been traditionally studied in the framework of datalog, a language
that restricts recursion to monotone queries over sets, which is guaranteed to converge in …
that restricts recursion to monotone queries over sets, which is guaranteed to converge in …